Skill UI

This guide helps researchers critically evaluate and sharpen their accounting research questions, ensuring the focus is on the social, organizational, or behavioral aspects of accounting practices, rather than purely financial or capital-market outcomes. It outlines the 'AOS fit' test and helps select the appropriate intellectual tradition for submission.

This tool guides the conceptual development of advanced accounting research manuscripts (CAR). It helps researchers build the core theoretical engine—the economic or behavioral mechanism, or the formal model—regardless of the methodology (e.g., archival, experimental, analytical). It ensures that hypotheses are directional, falsifiable, and rigorously grounded in established economic and accounting theory.

This skill reconstructs the full narrative behind a piece of code by analyzing local Git history. Instead of just naming the last author (like git blame), it traces the file's origin, tracks subsequent changes, identifies related companion files, and extracts intent clues from commit messages. Use this when you need to know *why* code exists before refactoring, making risky edits, or understanding complex system behavior.

A comprehensive methodological guide for structuring and writing robust mechanism analyses in empirical manuscripts, especially for rural economics. It stresses that mechanisms must be grounded in observable micro-level household or village behaviors (e.g., labor allocation, credit access), moving beyond macro-level narratives. The guide covers recommended paths (mediation, moderation, sub-sample comparison) and ethical writing practices.

This guide details the principles of conducting rigorous Monte Carlo simulations for econometric theory papers. It instructs users on designing simulations that test finite-sample behavior, ensuring that asymptotic approximations are useful and accurate across boundary cases (e.g., weak identification, heavy tails). Emphasis is placed on reproducibility, comprehensive metrics (bias, coverage, power), and ensuring the simulation supports the core theory.

A comprehensive guide for authors to sharpen the marginal contribution of their Experimental Economics (ExpEcon) manuscripts. It moves beyond simple topic novelty by outlining a structured ladder of contribution (e.g., confound removal, new decisive treatment) and teaching authors how to precisely map their design against canonical behavioral paradigms and prior work. Essential for improving academic rigor and manuscript acceptance rates.

A structured guide on translating behavioral or game-theoretic arguments into pre-specified, quantitative, and testable hypotheses for Experimental Economics (ExpEcon) manuscripts. This methodology emphasizes moving beyond informal intuition by defining the experimental game, deriving benchmark predictions, layering competing behavioral accounts, and generating comparative-statics hypotheses that treatments must adjudicate. It is essential for manuscripts aiming to robustly test theory through design.

This tool guides authors through the rigorous standards required for publishing in top experimental economics journals. It serves as a comprehensive checklist, evaluating a manuscript's fit, methodological strength, design transparency, and structural requirements (e.g., pre-registration, incentive-compatibility) against best practices in behavioral and experimental economics.

This guide serves as a comprehensive pre-submission self-check tool for authors targeting the journal Games and Economic Behavior (GEB). It details the journal's scope, required game-theoretic contributions (e.g., new models, equilibrium results, mechanisms), methodological rigor, and adherence to house style. It helps authors assess if their work is genuinely game-theoretic and provides guidance on re-framing strategies and potential alternative venues.

A comprehensive guide for academics on structuring and articulating the core, novel contribution of a scholarly paper, particularly in specialized fields like Game Theory and Economic Behavior. It provides a framework for crafting a single, highly impactful 'contribution sentence' and organizing the claim cascade (Headline, Why Open, Key Idea), ensuring the theoretical advance is immediately legible to specialized editors and reviewers.

A rigorous self-assessment tool for academic manuscripts in game theory and economic behavior. It guides the identification of core assumptions, tests the logical architecture of proofs, and verifies the generalizability of results. It covers both theoretical proofs (e.g., equilibrium, mechanism design) and experimental designs, ensuring the argument withstands specialist scrutiny.

This guide assists authors planning to submit to Games and Economic Behavior (GEB) by detailing best practices for data and code sharing. It clarifies that while data deposition is strongly encouraged for reproducibility, it is not a mandatory requirement. It outlines what to prepare, including raw data, analysis scripts, experimental instructions, and proper availability statements.